1. Field of the Invention
The present invention relates to image processing for detecting an alteration position of a photography image.
2. Description of the Related Art
The following technique for detecting alteration of an image photographed by a compact digital camera, single-lens reflex digital camera, or the like has been proposed. This technique detects alteration by analyzing a pattern originally included in a photography image and comparing feature amounts for respective regions without embedding any additional information such as a digital watermark in the photography image. Since no additional information such as a digital watermark is embedded, this technique can advantageously detect alteration without causing image quality deterioration of a photography image and an increase in processing time due to embedding of additional information.
Ahmet Emir Dirik, Nasir Memon “IMAGE TAMPER DETECTION BASED ON DEMOSAICING ARTIFACTS” ICIP 2009, pp. 1497-1500 (literature 1) estimates and analyzes a color filter array (CFA) pattern of an image sensor such as a CMOS sensor or charge coupled device (CCD) of a camera, and uses the CFA pattern in alteration detection. The CFA pattern is, for example, an RGB color filter arrangement, and indicates an RGB light-receiving pattern of each cell (a unit corresponding to a pixel in an image) of the image sensor.
Many image sensors distributed in the market have an arrangement in which each cell obtains color information of any of R, G, and B, so as to attain a cost reduction. The image sensor uses the CFA represented by a Bayer arrangement so as to efficiently obtain color information, and obtains color information from incoming light. The CFA is regularly and periodically arranged on the image sensor to have, for example, a square arrangement of 2×2 cells as a unit.
The technique of literature 1 estimates a CFA pattern of the image sensor from a full-color image using bilinear or bicubic interpolation processing, and detects a position where the periodicity of the estimated CFA pattern is corrupted as an alteration position, thus implementing alteration detection.
However, only four types of Bayer arrangements as CFA patterns used in many cameras are available. Therefore, although an image is altered, the CFA pattern may match that of an original photography image with probability of 1/4 to exhibit periodicity, and alteration may not be detected. In other words, a detection percentage of alteration detection using the CFA pattern is 75% at most.
When a CFA pattern is estimated using the bilinear or bicubic interpolation processing regardless of any demosaicing processing which develops a photography image, a wrong CFA pattern may be estimated. For this reason, the detection percentage of alteration detection often becomes lower.